In [1]:
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import statsmodels.api as sm
from statsmodels.stats.outliers_influence import variance_inflation_factor
from sklearn.model_selection import train_test_split, KFold
from sklearn.metrics import mean_squared_error, r2_score
from sklearn import linear_model
from sklearn.metrics import mean_absolute_error
from sklearn.metrics import median_absolute_error
from matplotlib.pylab import rcParams
import seaborn as sns                            # more plots
sns.set()

from dateutil.relativedelta import relativedelta # working with dates with style
from scipy.optimize import minimize              # for function minimization

import statsmodels.tsa.api as smt
import statsmodels.api as sm
import scipy.stats as scs

from itertools import product                    # some useful functions
from tqdm import tqdm_notebook
In [2]:
from sqlalchemy import create_engine, text
from datetime import datetime as dt
# Data Corabastos 
engine = create_engine('postgres://postgres:postADS4#@192.99.145.205:54328/ADR_DS4A')
precios_df = pd.read_sql_table("adr_corabastos_prices",con=engine,  
                  parse_dates=['cor_date'])

precios_df.columns = ['id', 'Fecha' ,'Categorias','Producto','Presentación','Cantidad','Unidad','Precio Calidad Extra','Precio Calidad Primera','Precio Calidad Corriente','Precio Grandes Superficies']


precios_df['Mes'] = pd.DatetimeIndex(precios_df['Fecha']).month
precios_df['Day'] = pd.DatetimeIndex(precios_df['Fecha']).dayofyear
precios_df['Day_m'] = pd.DatetimeIndex(precios_df['Fecha']).day
precios_df['Period'] = pd.to_datetime(precios_df['Fecha']).dt.to_period("M")
ipc = pd.read_sql_table(    "adr_ipc",con=engine)
ipc['Period'] = ipc['ipc_fecha'].dt.to_period("M")
current_ipc = float(ipc[ipc['ipc_fecha']==dt.today().strftime("20%y-%m-01")]['ipc_valor'])
period = str(ipc[ipc['ipc_valor']==current_ipc]['Period'].iloc[0])
df_corriente = precios_df.merge(ipc, on="Period", how='left')
df_corriente['Precio (pesos corrientes)'] = df_corriente['Precio Calidad Primera']/df_corriente['ipc_valor']*current_ipc
In [3]:
###Import Data Clean###

# Price Data 
Price_data = pd.read_csv('General/Price_data.csv', index_col=['Year'], 
                  parse_dates=['Year'])

Price_data = Price_data.drop('CU', axis=1)
# Production_data
Production_data=pd.read_csv('General/Production_data.csv', index_col=['Year'], 
                  parse_dates=['Year'])
#Production_Resume_data
Production_Resume_data=pd.read_csv('General/Production_Resume_data.csv', index_col=['Year'], 
                  parse_dates=['Year'])


Top_product=['Leche', 'Leche no procesada','mantequilla y leche','Leche procesada','Leche deslactosada','Leche deslactosada','Leche entera','Leche en polvo','Leche evaporada'
,'Cafe y productos','Cafe','Platanos y otros','Platanos','Yuca','Granos de cacao''Miel''Verduras','Verduras frescas','Verduras de primera','Legumbres',
'Maiz','Aceite de maiz','Aguacate','Arroz']


#Price_data_top=Price_data[Price_data['Item'].str.contains("Cafe")]

Price_data_top=Price_data[Price_data['Item'].isin(Top_product)]
Production_data_top=Production_data[Production_data['Item'].isin(Top_product)]
Production_Resume_data_top=Production_Resume_data[Production_Resume_data['Item'].isin(Top_product)]
In [4]:
g = sns.FacetGrid(Price_data_top,col='Item',col_wrap=2, height=5, despine=True)
g = (g.map(sns.lineplot,data=Price_data_top["Value"],marker=".").set_titles("{col_name} "))
In [5]:
g = sns.FacetGrid(Production_data_top,col='Item',col_wrap=2, height=5, despine=True)
g = (g.map(sns.lineplot,data=Production_data_top["Value"],marker=".").set_titles("{col_name} "))
In [6]:
g = sns.FacetGrid(Production_Resume_data_top,col='Item',col_wrap=2, height=5, despine=True)
g = (g.map(sns.lineplot,data=Production_Resume_data_top["Value"],marker=".").set_titles("{col_name} "))
In [7]:
producto=['PAPA PASTUSA']
precios_df_P = precios_df[precios_df['Producto'].isin(producto)]
df_corriente_P = df_corriente[precios_df['Producto'].isin(producto)]
#df_corriente_P['Fecha']=pd.to_datetime(df_corriente_P['Fecha'])
In [8]:
df_corriente.dtypes
Out[8]:
id                                     int64
Fecha                         datetime64[ns]
Categorias                            object
Producto                              object
Presentación                          object
Cantidad                             float64
Unidad                                object
Precio Calidad Extra                   int64
Precio Calidad Primera                 int64
Precio Calidad Corriente               int64
Precio Grandes Superficies             int64
Mes                                    int64
Day                                    int64
Day_m                                  int64
Period                             period[M]
ipc_id                                 int64
ipc_fecha                     datetime64[ns]
ipc_valor                            float64
Precio (pesos corrientes)            float64
dtype: object
In [9]:
corriente_Y = df_corriente_P.groupby(df_corriente['Fecha'].dt.to_period('Y')).mean().reset_index()
corriente_M = df_corriente_P.groupby(df_corriente['Fecha'].dt.to_period('M')).mean().reset_index()
corriente_W = df_corriente_P.groupby(df_corriente['Fecha'].dt.to_period('W')).mean().reset_index()
In [10]:
precios_Y = precios_df_P.groupby(precios_df_P['Fecha'].dt.to_period('Y')).mean().reset_index()
precios_M = precios_df_P.groupby(precios_df_P['Fecha'].dt.to_period('M')).mean().reset_index()
precios_W = precios_df_P.groupby(precios_df_P['Fecha'].dt.to_period('W')).mean().reset_index()
In [11]:
precios_Y.head()
Out[11]:
Fecha id Cantidad Precio Calidad Extra Precio Calidad Primera Precio Calidad Corriente Precio Grandes Superficies Mes Day Day_m
0 2012 343439.155172 50.0 756.206897 715.603448 664.827586 1036.745690 6.633621 187.323276 15.892241
1 2013 383765.673554 50.0 738.347107 697.272727 651.735537 1558.264463 6.549587 183.859504 15.842975
2 2014 426159.692623 50.0 980.614754 937.581967 887.991803 1400.000000 6.532787 183.348361 15.860656
3 2015 470940.419476 50.0 1072.883895 1031.011236 982.696629 50946.816479 6.550562 183.782772 15.775281
4 2016 517625.973585 50.0 1305.988679 1264.803774 1216.705660 79245.283019 6.637736 187.184906 15.656604
In [12]:
precios_Y['Year'] = precios_Y['Fecha'].dt.year
precios_M['Year'] = precios_M['Fecha'].dt.year
precios_M['Month'] = precios_M['Fecha'].dt.month
precios_M['Theta'] = precios_M['Month']*360/12
precios_W['Month'] = precios_W['Fecha'].dt.month
precios_W['Year'] = precios_W['Fecha'].dt.year
In [13]:
precios_M.columns
Out[13]:
Index(['Fecha', 'id', 'Cantidad', 'Precio Calidad Extra',
       'Precio Calidad Primera', 'Precio Calidad Corriente',
       'Precio Grandes Superficies', 'Mes', 'Day', 'Day_m', 'Year', 'Month',
       'Theta'],
      dtype='object')
In [14]:
corriente_Y['Year'] = corriente_Y['Fecha'].dt.year
corriente_M['Year'] = corriente_M['Fecha'].dt.year
corriente_M['Month'] = corriente_M['Fecha'].dt.month
corriente_M['Theta'] = corriente_M['Month']*360/12
corriente_W['Month'] = corriente_W['Fecha'].dt.month
corriente_W['Year'] = corriente_W['Fecha'].dt.year
In [15]:
corriente_M.columns
Out[15]:
Index(['Fecha', 'id', 'Cantidad', 'Precio Calidad Extra',
       'Precio Calidad Primera', 'Precio Calidad Corriente',
       'Precio Grandes Superficies', 'Mes', 'Day', 'Day_m', 'ipc_id',
       'ipc_valor', 'Precio (pesos corrientes)', 'Year', 'Month', 'Theta'],
      dtype='object')
In [16]:
import plotly.express as px
df = precios_M
fig = px.line_polar(df, r="Precio Calidad Primera", theta="Theta", color="Year", line_close=True,
                    color_discrete_sequence=px.colors.sequential.Plasma_r,
                    template="plotly_dark")
fig.show()
In [17]:
import plotly.express as px
df = corriente_M
fig = px.line_polar(df, r="Precio (pesos corrientes)", theta="Theta", color="Year", line_close=True,
                    color_discrete_sequence = px.colors.sequential.Plasma_r, template="plotly_dark")
fig.show()
In [18]:
### Filtrar un solo producto ###
#Product=['Manzanas']
#Price_data_P=Price_data[Price_data['Item'].isin(Product)].sort_index()
#Production_data_P=Production_data[Production_data['Item'].isin(Product)].sort_index()
#Production_Resume_data_P=Production_Resume_data[Production_Resume_data['Item'].isin(['Tomate'])].sort_index()
#precios_df_P = precios_df[precios_df['Producto'].isin(['CAFE 500GR'])].sort_index()
#corriente_M = df_corriente[df_corriente['Producto'].isin(['CAFE 500GR'])].sort_index()
#Price_data_P=Price_data_P.groupby(Price_data_P.index).mean().rename(columns={0:'mean'})

Moving average

In [19]:
corriente_Y['Fecha'] = corriente_Y['Fecha'].astype(str)
corriente_Y['Fecha'] = pd.to_datetime(corriente_Y['Fecha'])
corriente_M['Fecha'] = corriente_M['Fecha'].astype(str)
corriente_M['Fecha'] = pd.to_datetime(corriente_M['Fecha'])
corriente_W['Fecha'] = corriente_W['Fecha'].astype(str).str.split('/',1,expand=True)
corriente_M['Fecha'] = pd.to_datetime(corriente_M['Fecha'])
In [20]:
df_corriente_P.head()
Out[20]:
id Fecha Categorias Producto Presentación Cantidad Unidad Precio Calidad Extra Precio Calidad Primera Precio Calidad Corriente Precio Grandes Superficies Mes Day Day_m Period ipc_id ipc_fecha ipc_valor Precio (pesos corrientes)
40 363392 2013-01-08 TUBERCULOS PAPA PASTUSA BULTO 50.0 KILO 600 560 520 3000 1 8 8 2013-01 121 2013-01-01 78.28 755.012775
214 363566 2013-01-09 TUBERCULOS PAPA PASTUSA BULTO 50.0 KILO 600 560 520 3000 1 9 9 2013-01 121 2013-01-01 78.28 755.012775
388 363740 2013-01-10 TUBERCULOS PAPA PASTUSA BULTO 50.0 KILO 600 560 520 3000 1 10 10 2013-01 121 2013-01-01 78.28 755.012775
562 363914 2013-01-11 TUBERCULOS PAPA PASTUSA BULTO 50.0 KILO 600 560 520 3000 1 11 11 2013-01 121 2013-01-01 78.28 755.012775
736 364088 2013-01-14 TUBERCULOS PAPA PASTUSA BULTO 50.0 KILO 600 560 520 3000 1 14 14 2013-01 121 2013-01-01 78.28 755.012775
In [21]:
corriente_Y = corriente_Y.set_index('Fecha')
corriente_M = corriente_M.set_index('Fecha')
corriente_W = corriente_W.set_index('Fecha')
df_corriente_P = df_corriente_P.set_index('Fecha').sort_index()
In [22]:
df_corriente_P.columns
Out[22]:
Index(['id', 'Categorias', 'Producto', 'Presentación', 'Cantidad', 'Unidad',
       'Precio Calidad Extra', 'Precio Calidad Primera',
       'Precio Calidad Corriente', 'Precio Grandes Superficies', 'Mes', 'Day',
       'Day_m', 'Period', 'ipc_id', 'ipc_fecha', 'ipc_valor',
       'Precio (pesos corrientes)'],
      dtype='object')
In [23]:
corriente_Y  = corriente_Y .drop([ 'id', 'Cantidad', 'Precio Calidad Extra', 'Precio Calidad Primera',
       'Precio Calidad Corriente', 'Precio Grandes Superficies', 'Mes', 'Day',
       'Day_m', 'ipc_id', 'ipc_valor', 'Year'], axis=1)

corriente_M = corriente_M.drop(['id', 'Cantidad', 'Precio Calidad Extra', 'Precio Calidad Primera',
       'Precio Calidad Corriente', 'Precio Grandes Superficies', 'Mes', 'Day',
       'Day_m', 'ipc_id', 'ipc_valor', 'Year',
       'Month', 'Theta'], axis=1)

corriente_W  = corriente_W.drop(['id', 'Cantidad', 'Precio Calidad Extra', 'Precio Calidad Primera',
       'Precio Calidad Corriente', 'Precio Grandes Superficies', 'Mes', 'Day',
       'Day_m', 'ipc_id', 'ipc_valor', 'Month','Year'], axis=1)

df_corriente_P  = df_corriente_P.drop(['id', 'Categorias', 'Producto', 'Presentación', 'Cantidad', 'Unidad',
       'Precio Calidad Extra', 'Precio Calidad Primera',
       'Precio Calidad Corriente', 'Precio Grandes Superficies', 'Mes', 'Day',
       'Day_m', 'Period', 'ipc_id', 'ipc_fecha', 'ipc_valor'], axis=1)
In [24]:
corriente_Y['Precio (pesos corrientes)']=corriente_Y['Precio (pesos corrientes)'].round(decimals=0).astype(int)
corriente_M['Precio (pesos corrientes)']=corriente_M['Precio (pesos corrientes)'].round(decimals=0).astype(int)
corriente_W['Precio (pesos corrientes)']=corriente_W['Precio (pesos corrientes)'].round(decimals=0).astype(int)
In [25]:
#Price_data_P = Price_data_P.drop(['Item Code'], axis=1)
#precios_df_P = precios_df_P.drop([ 'id', 'Categorias', 'Producto', 'Presentación', 'Cantidad', 'Unidad',
#'Precio Calidad Extra', 'Precio Calidad Corriente', 'Precio Grandes Superficies','Mes','Day','Day_m','Period'], axis=1)
#precios_df_P = precios_df_P.set_index('Fecha')
#precios_df_P = precios_df_P.sort_index(axis = 0)
In [26]:
def plotMovingAverage(series, window, plot_intervals=False, scale=1.96, 
                      plot_anomalies=False):

    """
        series - dataframe with timeseries
        window - rolling window size 
        plot_intervals - show confidence intervals
        plot_anomalies - show anomalies 

    """
    rolling_mean = series.rolling(window=window).mean()

    plt.figure(figsize=(15,5))
    plt.title("Moving average\n window size = {}".format(window))
    plt.plot(rolling_mean, "g", label="Rolling mean trend")

    # Plot confidence intervals for smoothed values
    if plot_intervals:
        mae = mean_absolute_error(series[window:], rolling_mean[window:])
        deviation = np.std(series[window:] - rolling_mean[window:])
        lower_bond = rolling_mean - (mae + scale * deviation)
        upper_bond = rolling_mean + (mae + scale * deviation)
        plt.plot(upper_bond, "r--", label="Upper Bond / Lower Bond")
        plt.plot(lower_bond, "r--")
        
        # Having the intervals, find abnormal values
        if plot_anomalies:
            anomalies = pd.DataFrame(index=series.index, columns=series.columns)
            anomalies[series<lower_bond] = series[series<lower_bond]
            anomalies[series>upper_bond] = series[series>upper_bond]
            plt.plot(anomalies, "ro", markersize=10)
        
    plt.plot(series[window:], label="Actual values")
    plt.legend(loc="upper left")
    plt.grid(True)
In [27]:
 plotMovingAverage(corriente_Y, 5)
In [28]:
 plotMovingAverage(corriente_M, 12)
In [29]:
 plotMovingAverage(corriente_W, 5)
In [30]:
 plotMovingAverage(df_corriente_P, 7)
In [31]:
plotMovingAverage(corriente_Y, 2, plot_intervals=True,plot_anomalies=True)
In [32]:
plotMovingAverage(corriente_M, 12, plot_intervals=True,plot_anomalies=True)
In [33]:
plotMovingAverage(corriente_W, 7, plot_intervals=True,plot_anomalies=True)
In [34]:
plotMovingAverage(df_corriente_P, 7, plot_intervals=True, plot_anomalies=True)
In [35]:
def plotProcess(x,rho=0):
    w = x 
    for t in range(len(x)):
        x[t] = rho * x[t-1] + w[t]

    with plt.style.context('bmh'):  
        plt.figure(figsize=(10, 3))
        plt.plot(x)
        plt.title("Rho {}\n Dickey-Fuller p-value: {}".format(rho, round(sm.tsa.stattools.adfuller(x)[1], 3))) 
In [36]:
for rho in [0, 0.6, 0.9, 1]:
    plotProcess(corriente_Y['Precio (pesos corrientes)'].values,rho=rho)
In [37]:
for rho in [0, 0.6, 0.9, 1]:
    plotProcess( corriente_M['Precio (pesos corrientes)'].values,rho=rho)
In [38]:
for rho in [0, 0.6, 0.9, 1]:
    plotProcess( corriente_W['Precio (pesos corrientes)'].values,rho=rho)
In [39]:
for rho in [0, 0.6, 0.9, 1]:
    plotProcess( corriente_W['Precio (pesos corrientes)'].values,rho=rho)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\ipykernel_launcher.py:4: RuntimeWarning:

overflow encountered in long_scalars

In [40]:
for rho in [0, 0.6, 0.9, 1]:
    plotProcess( df_corriente_P['Precio (pesos corrientes)'].values,rho=rho)

Augmented Dickey-Fuller test

In [41]:
X = corriente_Y['Precio (pesos corrientes)']
result = sm.tsa.stattools.adfuller(X)
print('ADF Statistic: %f' % result[0])
print('p-value: %f' % result[1])
print('Critical Values:')
for key, value in result[4].items():
	print('\t%s: %.3f' % (key, value))
ADF Statistic: -1.201405
p-value: 0.672991
Critical Values:
	1%: -4.939
	5%: -3.478
	10%: -2.844
In [42]:
X =corriente_M['Precio (pesos corrientes)']
result = sm.tsa.stattools.adfuller(X)
print('ADF Statistic: %f' % result[0])
print('p-value: %f' % result[1])
print('Critical Values:')
for key, value in result[4].items():
	print('\t%s: %.3f' % (key, value))
ADF Statistic: -1.129477
p-value: 0.703175
Critical Values:
	1%: -3.498
	5%: -2.891
	10%: -2.583
In [43]:
X =corriente_W['Precio (pesos corrientes)']
result = sm.tsa.stattools.adfuller(X)
print('ADF Statistic: %f' % result[0])
print('p-value: %f' % result[1])
print('Critical Values:')
for key, value in result[4].items():
	print('\t%s: %.3f' % (key, value))
ADF Statistic: -6.928523
p-value: 0.000000
Critical Values:
	1%: -3.445
	5%: -2.868
	10%: -2.570
In [44]:
X =df_corriente_P['Precio (pesos corrientes)']
result = sm.tsa.stattools.adfuller(X)
print('ADF Statistic: %f' % result[0])
print('p-value: %f' % result[1])
print('Critical Values:')
for key, value in result[4].items():
	print('\t%s: %.3f' % (key, value))
ADF Statistic: -0.174483
p-value: 0.941496
Critical Values:
	1%: -3.433
	5%: -2.863
	10%: -2.567
In [45]:
def tsplot(y, lags=None, figsize=(12, 7), style='bmh'):
    """
        Plot time series, its ACF and PACF, calculate Dickey–Fuller test
        
        y - timeseries
        lags - how many lags to include in ACF, PACF calculation
    """
    if not isinstance(y, pd.Series):
        y = pd.Series(y)
        
    with plt.style.context(style):    
        fig = plt.figure(figsize=figsize)
        layout = (2, 2)
        ts_ax = plt.subplot2grid(layout, (0, 0), colspan=2)
        acf_ax = plt.subplot2grid(layout, (1, 0))
        pacf_ax = plt.subplot2grid(layout, (1, 1))
        
        y.plot(ax=ts_ax)
        p_value = sm.tsa.stattools.adfuller(y)[1]
        ts_ax.set_title('Time Series Analysis Plots\n Dickey-Fuller: p={0:.5f}'.format(p_value))
        smt.graphics.plot_acf(y, lags=lags, ax=acf_ax)
        smt.graphics.plot_pacf(y, lags=lags, ax=pacf_ax)
        plt.tight_layout()
In [46]:
tsplot(df_corriente_P['Precio (pesos corrientes)'], lags=6)
In [47]:
tsplot(corriente_M['Precio (pesos corrientes)'], lags=100)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\regression\linear_model.py:1406: RuntimeWarning:

invalid value encountered in sqrt

In [48]:
tsplot(corriente_W['Precio (pesos corrientes)'], lags=200)
In [49]:
tsplot(df_corriente_P['Precio (pesos corrientes)'], lags=200)
In [50]:
corriente_Y_diff = corriente_Y['Precio (pesos corrientes)'] - corriente_Y['Precio (pesos corrientes)'].shift(1)
tsplot(corriente_Y_diff[1:], lags=6)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\regression\linear_model.py:1406: RuntimeWarning:

invalid value encountered in sqrt

In [51]:
corriente_M_diff = corriente_M['Precio (pesos corrientes)'] - corriente_M['Precio (pesos corrientes)'].shift(40)
tsplot(corriente_M_diff [40:], lags=60)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\regression\linear_model.py:1406: RuntimeWarning:

invalid value encountered in sqrt

In [52]:
corriente_W_diff = corriente_W['Precio (pesos corrientes)'] - corriente_W['Precio (pesos corrientes)'].shift(1)
tsplot(corriente_W_diff[1:], lags=60)
In [ ]:
 
In [53]:
df_corriente_P_diff = df_corriente_P['Precio (pesos corrientes)'] - df_corriente_P['Precio (pesos corrientes)'].shift(180)
tsplot(df_corriente_P_diff[180:], lags=60)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\regression\linear_model.py:1406: RuntimeWarning:

invalid value encountered in sqrt

In [54]:
ps = range(1, 4)
d=1 
qs = range(1, 4)
Ps = range(0, 3)
D=1 
Qs = range(0, 3)
s = 8
parameters = product(ps, qs, Ps, Qs)
parameters_list = list(parameters)
len(parameters_list)
Out[54]:
81
In [55]:
def optimizeSARIMA(parameters_list, d, D, s):
    """
        Return dataframe with parameters and corresponding AIC
        
        parameters_list - list with (p, q, P, Q) tuples
        d - integration order in ARIMA model
        D - seasonal integration order 
        s - length of season
    """
    
    results = []
    best_aic = float("inf")

    for param in tqdm_notebook(parameters_list):
        # we need try-except because on some combinations model fails to converge
        try:
            model=sm.tsa.statespace.SARIMAX(corriente_M['Precio (pesos corrientes)'], order=(param[0], d, param[1]), 
                                            seasonal_order=(param[2], D, param[3], s)).fit(disp=-1)
        except:
            continue
        aic = model.aic
        # saving best model, AIC and parameters
        if aic < best_aic:
            best_model = model
            best_aic = aic
            best_param = param
        results.append([param, model.aic])

    result_table = pd.DataFrame(results)
    result_table.columns = ['parameters', 'aic']
    # sorting in ascending order, the lower AIC is - the better
    result_table = result_table.sort_values(by='aic', ascending=True).reset_index(drop=True)
    
    return result_table
In [56]:
%%time
result_table_M = optimizeSARIMA(parameters_list, d, D, s)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\ipykernel_launcher.py:14: TqdmDeprecationWarning:

This function will be removed in tqdm==5.0.0
Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\statespace\sarimax.py:975: UserWarning:

Non-invertible starting MA parameters found. Using zeros as starting parameters.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1006: UserWarning:

Non-invertible starting seasonal moving average Using zeros as starting parameters.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

Wall time: 2min 57s
In [57]:
result_table_M.head(40)
Out[57]:
parameters aic
0 (3, 3, 0, 2) 1529.102554
1 (3, 3, 1, 1) 1529.863974
2 (2, 3, 0, 2) 1530.088732
3 (3, 1, 0, 2) 1530.563337
4 (2, 3, 1, 1) 1530.739842
5 (3, 1, 0, 1) 1530.910125
6 (2, 3, 0, 1) 1531.184092
7 (3, 1, 1, 1) 1531.201838
8 (2, 3, 1, 2) 1531.342445
9 (3, 2, 0, 2) 1531.343112
10 (2, 3, 2, 1) 1531.597240
11 (3, 1, 2, 1) 1531.799447
12 (3, 3, 0, 1) 1532.032494
13 (3, 2, 1, 1) 1532.071126
14 (3, 2, 0, 1) 1532.409465
15 (3, 2, 2, 1) 1533.013086
16 (3, 3, 2, 1) 1534.565983
17 (2, 3, 2, 2) 1534.725616
18 (3, 1, 1, 2) 1535.044311
19 (3, 3, 1, 2) 1537.134219
20 (3, 1, 2, 0) 1539.939749
21 (3, 3, 2, 0) 1540.258413
22 (3, 2, 2, 0) 1541.375830
23 (2, 2, 0, 2) 1541.767691
24 (2, 2, 2, 1) 1542.692783
25 (2, 2, 1, 1) 1542.971764
26 (2, 2, 0, 1) 1543.763596
27 (2, 2, 1, 2) 1543.827271
28 (2, 3, 2, 0) 1544.759377
29 (3, 2, 1, 2) 1545.897191
30 (3, 3, 2, 2) 1546.243720
31 (2, 2, 2, 2) 1547.687971
32 (3, 1, 2, 2) 1549.662068
33 (2, 1, 2, 1) 1549.725131
34 (2, 1, 0, 2) 1549.963490
35 (2, 1, 1, 2) 1550.738915
36 (2, 1, 2, 2) 1551.035926
37 (2, 1, 1, 1) 1551.146602
38 (2, 1, 0, 1) 1552.451320
39 (2, 3, 1, 0) 1554.396191
In [58]:
p, q, P, Q = result_table_M.parameters[0]

best_model=sm.tsa.statespace.SARIMAX(corriente_M['Precio (pesos corrientes)'], order=(p, d, q), 
                                        seasonal_order=(P, D, Q, s)).fit(disp=-1)
print(best_model.summary())
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:162: ValueWarning:

No frequency information was provided, so inferred frequency MS will be used.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1006: UserWarning:

Non-invertible starting seasonal moving average Using zeros as starting parameters.

                                       SARIMAX Results                                        
==============================================================================================
Dep. Variable:              Precio (pesos corrientes)   No. Observations:                  103
Model:             SARIMAX(3, 1, 3)x(0, 1, [1, 2], 8)   Log Likelihood                -755.551
Date:                                Sun, 02 Aug 2020   AIC                           1529.103
Time:                                        12:13:02   BIC                           1551.992
Sample:                                    01-01-2012   HQIC                          1538.348
                                         - 07-01-2020                                         
Covariance Type:                                  opg                                         
==============================================================================
                 coef    std err          z      P>|z|      [0.025      0.975]
------------------------------------------------------------------------------
ar.L1          2.1387      0.157     13.656      0.000       1.832       2.446
ar.L2         -1.5384      0.286     -5.372      0.000      -2.100      -0.977
ar.L3          0.3997      0.132      3.027      0.002       0.141       0.659
ma.L1          0.3818      0.173      2.204      0.028       0.042       0.721
ma.L2          0.3359      0.117      2.863      0.004       0.106       0.566
ma.L3          0.3375      0.100      3.389      0.001       0.142       0.533
ma.S.L8       -0.9815      0.096    -10.184      0.000      -1.170      -0.793
ma.S.L16       0.2333      0.084      2.775      0.006       0.069       0.398
sigma2      2.221e+04   2578.492      8.613      0.000    1.72e+04    2.73e+04
===================================================================================
Ljung-Box (Q):                       15.49   Jarque-Bera (JB):              4728.76
Prob(Q):                              1.00   Prob(JB):                         0.00
Heteroskedasticity (H):               0.06   Skew:                             4.49
Prob(H) (two-sided):                  0.00   Kurtosis:                        36.57
===================================================================================

Warnings:
[1] Covariance matrix calculated using the outer product of gradients (complex-step).
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

In [59]:
def optimizeSARIMA(parameters_list, d, D, s):
    """
        Return dataframe with parameters and corresponding AIC
        
        parameters_list - list with (p, q, P, Q) tuples
        d - integration order in ARIMA model
        D - seasonal integration order 
        s - length of season
    """
    
    results = []
    best_aic = float("inf")

    for param in tqdm_notebook(parameters_list):
        # we need try-except because on some combinations model fails to converge
        try:
            model=sm.tsa.statespace.SARIMAX(corriente_W['Precio (pesos corrientes)'], order=(param[0], d, param[1]), 
                                            seasonal_order=(param[2], D, param[3], s)).fit(disp=-1)
        except:
            continue
        aic = model.aic
        # saving best model, AIC and parameters
        if aic < best_aic:
            best_model = model
            best_aic = aic
            best_param = param
        results.append([param, model.aic])

    result_table = pd.DataFrame(results)
    result_table.columns = ['parameters', 'aic']
    # sorting in ascending order, the lower AIC is - the better
    result_table = result_table.sort_values(by='aic', ascending=True).reset_index(drop=True)
    
    return result_table
In [ ]:
%%time
result_table_W = optimizeSARIMA(parameters_list, d, D, s)
C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\ipykernel_launcher.py:14: TqdmDeprecationWarning:

This function will be removed in tqdm==5.0.0
Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\statespace\sarimax.py:975: UserWarning:

Non-invertible starting MA parameters found. Using zeros as starting parameters.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\base\model.py:568: ConvergenceWarning:

Maximum Likelihood optimization failed to converge. Check mle_retvals

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

C:\Users\57314\anaconda3\envs\Ds4a\lib\site-packages\statsmodels\tsa\base\tsa_model.py:218: ValueWarning:

A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.

In [ ]:
result_table_W.head(20)
In [ ]:
p, q, P, Q = result_table_W.parameters[0]

best_model=sm.tsa.statespace.SARIMAX(corriente_W['Precio (pesos corrientes)'], order=(p, d, q), 
                                        seasonal_order=(P, D, Q, s)).fit(disp=-1)
print(best_model.summary())
In [ ]:
print(mle_retvals)
In [ ]:
tsplot(best_model.resid[+1:], lags=60)
In [ ]: